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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationMon, 30 Nov 2009 11:40:52 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/Nov/30/t1259607106ij5411mjywpg0hk.htm/, Retrieved Wed, 01 May 2024 22:34:47 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=61858, Retrieved Wed, 01 May 2024 22:34:47 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact121

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-12 13:32:37] [76963dc1903f0f612b6153510a3818cf]
- R  D  [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-17 12:14:40] [76963dc1903f0f612b6153510a3818cf]
-         [Univariate Explorative Data Analysis] [Run Sequence Plot...] [2008-12-22 18:19:51] [1ce0d16c8f4225c977b42c8fa93bc163]
- RMP       [(Partial) Autocorrelation Function] [Identifying Integ...] [2009-11-22 12:26:39] [b98453cac15ba1066b407e146608df68]
- R  D        [(Partial) Autocorrelation Function] [ACF Link 3] [2009-11-25 19:08:54] [1f74ef2f756548f1f3a7b6136ea56d7f]
-   PD            [(Partial) Autocorrelation Function] [review WS 8 autoc...] [2009-11-30 18:40:52] [51d49d3536f6a59f2486a67bf50b2759] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
5250.0
3937.0
4004.0
5560.0
3922.0
3759.0
4138.0
4634.0
3996.0
4308.0
4143.0
4429.0
5219.0
4929.0
5755.0
5592.0
4163.0
4962.0
5208.0
4755.0
4491.0
5732.0
5731.0
5040.0
6102.0
4904.0
5369.0
5578.0
4619.0
4731.0
5011.0
5299.0
4146.0
4625.0
4736.0
4219.0
5116.0
4205.0
4121.0
5103.0
4300.0
4578.0
3809.0
5526.0
4247.0
3830.0
4394.0
4826.0
4409.0
4569.0
4106.0
4794.0
3914.0
3793.0
4405.0
4022.0
4100.0
4788.0
3163.0
3585.0
3903.0

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=61858&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=61858&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61858&T=0

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.46822-3.62680.000297
2-0.18352-1.42150.080169
30.2584212.00170.024921
4-0.025749-0.19950.421292
5-0.058696-0.45470.325497
6-0.025517-0.19770.421991
70.0459060.35560.361699
8-0.042326-0.32790.372082
90.0426380.33030.371172
100.0785680.60860.272549
11-0.259105-2.0070.02463
120.2779432.15290.017677
13-0.153632-1.190.119362
14-0.017885-0.13850.44514
150.0951540.73710.23198
16-0.065119-0.50440.307911
17-0.026902-0.20840.417818
180.0580640.44980.327253
190.0324620.25140.401163
20-0.182005-1.40980.08188
210.1617671.2530.107526
22-0.011797-0.09140.463747
23-0.144702-1.12090.133408
240.1549381.20010.117401
25-0.061236-0.47430.318493
26-0.000694-0.00540.497865
270.0343910.26640.395424
28-0.008969-0.06950.472422
29-0.02265-0.17540.43066
300.0560550.43420.33285
31-0.032592-0.25250.400775
32-0.075926-0.58810.279329
330.149721.15970.125378
34-0.055971-0.43360.333084
35-0.124252-0.96250.169843
360.1942921.5050.068788

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.46822 & -3.6268 & 0.000297 \tabularnewline
2 & -0.18352 & -1.4215 & 0.080169 \tabularnewline
3 & 0.258421 & 2.0017 & 0.024921 \tabularnewline
4 & -0.025749 & -0.1995 & 0.421292 \tabularnewline
5 & -0.058696 & -0.4547 & 0.325497 \tabularnewline
6 & -0.025517 & -0.1977 & 0.421991 \tabularnewline
7 & 0.045906 & 0.3556 & 0.361699 \tabularnewline
8 & -0.042326 & -0.3279 & 0.372082 \tabularnewline
9 & 0.042638 & 0.3303 & 0.371172 \tabularnewline
10 & 0.078568 & 0.6086 & 0.272549 \tabularnewline
11 & -0.259105 & -2.007 & 0.02463 \tabularnewline
12 & 0.277943 & 2.1529 & 0.017677 \tabularnewline
13 & -0.153632 & -1.19 & 0.119362 \tabularnewline
14 & -0.017885 & -0.1385 & 0.44514 \tabularnewline
15 & 0.095154 & 0.7371 & 0.23198 \tabularnewline
16 & -0.065119 & -0.5044 & 0.307911 \tabularnewline
17 & -0.026902 & -0.2084 & 0.417818 \tabularnewline
18 & 0.058064 & 0.4498 & 0.327253 \tabularnewline
19 & 0.032462 & 0.2514 & 0.401163 \tabularnewline
20 & -0.182005 & -1.4098 & 0.08188 \tabularnewline
21 & 0.161767 & 1.253 & 0.107526 \tabularnewline
22 & -0.011797 & -0.0914 & 0.463747 \tabularnewline
23 & -0.144702 & -1.1209 & 0.133408 \tabularnewline
24 & 0.154938 & 1.2001 & 0.117401 \tabularnewline
25 & -0.061236 & -0.4743 & 0.318493 \tabularnewline
26 & -0.000694 & -0.0054 & 0.497865 \tabularnewline
27 & 0.034391 & 0.2664 & 0.395424 \tabularnewline
28 & -0.008969 & -0.0695 & 0.472422 \tabularnewline
29 & -0.02265 & -0.1754 & 0.43066 \tabularnewline
30 & 0.056055 & 0.4342 & 0.33285 \tabularnewline
31 & -0.032592 & -0.2525 & 0.400775 \tabularnewline
32 & -0.075926 & -0.5881 & 0.279329 \tabularnewline
33 & 0.14972 & 1.1597 & 0.125378 \tabularnewline
34 & -0.055971 & -0.4336 & 0.333084 \tabularnewline
35 & -0.124252 & -0.9625 & 0.169843 \tabularnewline
36 & 0.194292 & 1.505 & 0.068788 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=61858&T=1

[TABLE]
[ROW][C]Autocorrelation Function[/C][/ROW]
[ROW][C]Time lag k[/C][C]ACF(k)[/C][C]T-STAT[/C][C]P-value[/C][/ROW]
[ROW][C]1[/C][C]-0.46822[/C][C]-3.6268[/C][C]0.000297[/C][/ROW]
[ROW][C]2[/C][C]-0.18352[/C][C]-1.4215[/C][C]0.080169[/C][/ROW]
[ROW][C]3[/C][C]0.258421[/C][C]2.0017[/C][C]0.024921[/C][/ROW]
[ROW][C]4[/C][C]-0.025749[/C][C]-0.1995[/C][C]0.421292[/C][/ROW]
[ROW][C]5[/C][C]-0.058696[/C][C]-0.4547[/C][C]0.325497[/C][/ROW]
[ROW][C]6[/C][C]-0.025517[/C][C]-0.1977[/C][C]0.421991[/C][/ROW]
[ROW][C]7[/C][C]0.045906[/C][C]0.3556[/C][C]0.361699[/C][/ROW]
[ROW][C]8[/C][C]-0.042326[/C][C]-0.3279[/C][C]0.372082[/C][/ROW]
[ROW][C]9[/C][C]0.042638[/C][C]0.3303[/C][C]0.371172[/C][/ROW]
[ROW][C]10[/C][C]0.078568[/C][C]0.6086[/C][C]0.272549[/C][/ROW]
[ROW][C]11[/C][C]-0.259105[/C][C]-2.007[/C][C]0.02463[/C][/ROW]
[ROW][C]12[/C][C]0.277943[/C][C]2.1529[/C][C]0.017677[/C][/ROW]
[ROW][C]13[/C][C]-0.153632[/C][C]-1.19[/C][C]0.119362[/C][/ROW]
[ROW][C]14[/C][C]-0.017885[/C][C]-0.1385[/C][C]0.44514[/C][/ROW]
[ROW][C]15[/C][C]0.095154[/C][C]0.7371[/C][C]0.23198[/C][/ROW]
[ROW][C]16[/C][C]-0.065119[/C][C]-0.5044[/C][C]0.307911[/C][/ROW]
[ROW][C]17[/C][C]-0.026902[/C][C]-0.2084[/C][C]0.417818[/C][/ROW]
[ROW][C]18[/C][C]0.058064[/C][C]0.4498[/C][C]0.327253[/C][/ROW]
[ROW][C]19[/C][C]0.032462[/C][C]0.2514[/C][C]0.401163[/C][/ROW]
[ROW][C]20[/C][C]-0.182005[/C][C]-1.4098[/C][C]0.08188[/C][/ROW]
[ROW][C]21[/C][C]0.161767[/C][C]1.253[/C][C]0.107526[/C][/ROW]
[ROW][C]22[/C][C]-0.011797[/C][C]-0.0914[/C][C]0.463747[/C][/ROW]
[ROW][C]23[/C][C]-0.144702[/C][C]-1.1209[/C][C]0.133408[/C][/ROW]
[ROW][C]24[/C][C]0.154938[/C][C]1.2001[/C][C]0.117401[/C][/ROW]
[ROW][C]25[/C][C]-0.061236[/C][C]-0.4743[/C][C]0.318493[/C][/ROW]
[ROW][C]26[/C][C]-0.000694[/C][C]-0.0054[/C][C]0.497865[/C][/ROW]
[ROW][C]27[/C][C]0.034391[/C][C]0.2664[/C][C]0.395424[/C][/ROW]
[ROW][C]28[/C][C]-0.008969[/C][C]-0.0695[/C][C]0.472422[/C][/ROW]
[ROW][C]29[/C][C]-0.02265[/C][C]-0.1754[/C][C]0.43066[/C][/ROW]
[ROW][C]30[/C][C]0.056055[/C][C]0.4342[/C][C]0.33285[/C][/ROW]
[ROW][C]31[/C][C]-0.032592[/C][C]-0.2525[/C][C]0.400775[/C][/ROW]
[ROW][C]32[/C][C]-0.075926[/C][C]-0.5881[/C][C]0.279329[/C][/ROW]
[ROW][C]33[/C][C]0.14972[/C][C]1.1597[/C][C]0.125378[/C][/ROW]
[ROW][C]34[/C][C]-0.055971[/C][C]-0.4336[/C][C]0.333084[/C][/ROW]
[ROW][C]35[/C][C]-0.124252[/C][C]-0.9625[/C][C]0.169843[/C][/ROW]
[ROW][C]36[/C][C]0.194292[/C][C]1.505[/C][C]0.068788[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=61858&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61858&T=1

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.46822-3.62680.000297
2-0.18352-1.42150.080169
30.2584212.00170.024921
4-0.025749-0.19950.421292
5-0.058696-0.45470.325497
6-0.025517-0.19770.421991
70.0459060.35560.361699
8-0.042326-0.32790.372082
90.0426380.33030.371172
100.0785680.60860.272549
11-0.259105-2.0070.02463
120.2779432.15290.017677
13-0.153632-1.190.119362
14-0.017885-0.13850.44514
150.0951540.73710.23198
16-0.065119-0.50440.307911
17-0.026902-0.20840.417818
180.0580640.44980.327253
190.0324620.25140.401163
20-0.182005-1.40980.08188
210.1617671.2530.107526
22-0.011797-0.09140.463747
23-0.144702-1.12090.133408
240.1549381.20010.117401
25-0.061236-0.47430.318493
26-0.000694-0.00540.497865
270.0343910.26640.395424
28-0.008969-0.06950.472422
29-0.02265-0.17540.43066
300.0560550.43420.33285
31-0.032592-0.25250.400775
32-0.075926-0.58810.279329
330.149721.15970.125378
34-0.055971-0.43360.333084
35-0.124252-0.96250.169843
360.1942921.5050.068788






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.46822-3.62680.000297
2-0.515836-3.99578.9e-05
3-0.197824-1.53230.065348
4-0.052715-0.40830.342244
50.0543070.42070.337753
6-0.026723-0.2070.418357
7-0.03643-0.28220.389385
8-0.118231-0.91580.181716
9-0.02475-0.19170.424307
100.1682041.30290.098793
11-0.151148-1.17080.123156
120.1031860.79930.213642
13-0.162362-1.25770.106695
14-0.052807-0.4090.341983
15-0.030539-0.23660.406904
16-0.000494-0.00380.498478
17-0.079454-0.61550.270292
18-0.027648-0.21420.415574
190.0324330.25120.401248
20-0.186344-1.44340.077052
210.0152560.11820.453162
22-0.142095-1.10070.13772
23-0.07273-0.56340.287643
24-0.094026-0.72830.234626
25-0.059688-0.46230.322755
26-0.020765-0.16080.436378
270.0055160.04270.483031
280.0295290.22870.409927
29-0.022961-0.17790.429717
300.1186770.91930.180818
31-0.08249-0.6390.262639
32-0.017513-0.13570.446273
33-0.025479-0.19740.422107
340.0225380.17460.430999
35-0.100132-0.77560.22051
360.0259990.20140.420538

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.46822 & -3.6268 & 0.000297 \tabularnewline
2 & -0.515836 & -3.9957 & 8.9e-05 \tabularnewline
3 & -0.197824 & -1.5323 & 0.065348 \tabularnewline
4 & -0.052715 & -0.4083 & 0.342244 \tabularnewline
5 & 0.054307 & 0.4207 & 0.337753 \tabularnewline
6 & -0.026723 & -0.207 & 0.418357 \tabularnewline
7 & -0.03643 & -0.2822 & 0.389385 \tabularnewline
8 & -0.118231 & -0.9158 & 0.181716 \tabularnewline
9 & -0.02475 & -0.1917 & 0.424307 \tabularnewline
10 & 0.168204 & 1.3029 & 0.098793 \tabularnewline
11 & -0.151148 & -1.1708 & 0.123156 \tabularnewline
12 & 0.103186 & 0.7993 & 0.213642 \tabularnewline
13 & -0.162362 & -1.2577 & 0.106695 \tabularnewline
14 & -0.052807 & -0.409 & 0.341983 \tabularnewline
15 & -0.030539 & -0.2366 & 0.406904 \tabularnewline
16 & -0.000494 & -0.0038 & 0.498478 \tabularnewline
17 & -0.079454 & -0.6155 & 0.270292 \tabularnewline
18 & -0.027648 & -0.2142 & 0.415574 \tabularnewline
19 & 0.032433 & 0.2512 & 0.401248 \tabularnewline
20 & -0.186344 & -1.4434 & 0.077052 \tabularnewline
21 & 0.015256 & 0.1182 & 0.453162 \tabularnewline
22 & -0.142095 & -1.1007 & 0.13772 \tabularnewline
23 & -0.07273 & -0.5634 & 0.287643 \tabularnewline
24 & -0.094026 & -0.7283 & 0.234626 \tabularnewline
25 & -0.059688 & -0.4623 & 0.322755 \tabularnewline
26 & -0.020765 & -0.1608 & 0.436378 \tabularnewline
27 & 0.005516 & 0.0427 & 0.483031 \tabularnewline
28 & 0.029529 & 0.2287 & 0.409927 \tabularnewline
29 & -0.022961 & -0.1779 & 0.429717 \tabularnewline
30 & 0.118677 & 0.9193 & 0.180818 \tabularnewline
31 & -0.08249 & -0.639 & 0.262639 \tabularnewline
32 & -0.017513 & -0.1357 & 0.446273 \tabularnewline
33 & -0.025479 & -0.1974 & 0.422107 \tabularnewline
34 & 0.022538 & 0.1746 & 0.430999 \tabularnewline
35 & -0.100132 & -0.7756 & 0.22051 \tabularnewline
36 & 0.025999 & 0.2014 & 0.420538 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=61858&T=2

[TABLE]
[ROW][C]Partial Autocorrelation Function[/C][/ROW]
[ROW][C]Time lag k[/C][C]PACF(k)[/C][C]T-STAT[/C][C]P-value[/C][/ROW]
[ROW][C]1[/C][C]-0.46822[/C][C]-3.6268[/C][C]0.000297[/C][/ROW]
[ROW][C]2[/C][C]-0.515836[/C][C]-3.9957[/C][C]8.9e-05[/C][/ROW]
[ROW][C]3[/C][C]-0.197824[/C][C]-1.5323[/C][C]0.065348[/C][/ROW]
[ROW][C]4[/C][C]-0.052715[/C][C]-0.4083[/C][C]0.342244[/C][/ROW]
[ROW][C]5[/C][C]0.054307[/C][C]0.4207[/C][C]0.337753[/C][/ROW]
[ROW][C]6[/C][C]-0.026723[/C][C]-0.207[/C][C]0.418357[/C][/ROW]
[ROW][C]7[/C][C]-0.03643[/C][C]-0.2822[/C][C]0.389385[/C][/ROW]
[ROW][C]8[/C][C]-0.118231[/C][C]-0.9158[/C][C]0.181716[/C][/ROW]
[ROW][C]9[/C][C]-0.02475[/C][C]-0.1917[/C][C]0.424307[/C][/ROW]
[ROW][C]10[/C][C]0.168204[/C][C]1.3029[/C][C]0.098793[/C][/ROW]
[ROW][C]11[/C][C]-0.151148[/C][C]-1.1708[/C][C]0.123156[/C][/ROW]
[ROW][C]12[/C][C]0.103186[/C][C]0.7993[/C][C]0.213642[/C][/ROW]
[ROW][C]13[/C][C]-0.162362[/C][C]-1.2577[/C][C]0.106695[/C][/ROW]
[ROW][C]14[/C][C]-0.052807[/C][C]-0.409[/C][C]0.341983[/C][/ROW]
[ROW][C]15[/C][C]-0.030539[/C][C]-0.2366[/C][C]0.406904[/C][/ROW]
[ROW][C]16[/C][C]-0.000494[/C][C]-0.0038[/C][C]0.498478[/C][/ROW]
[ROW][C]17[/C][C]-0.079454[/C][C]-0.6155[/C][C]0.270292[/C][/ROW]
[ROW][C]18[/C][C]-0.027648[/C][C]-0.2142[/C][C]0.415574[/C][/ROW]
[ROW][C]19[/C][C]0.032433[/C][C]0.2512[/C][C]0.401248[/C][/ROW]
[ROW][C]20[/C][C]-0.186344[/C][C]-1.4434[/C][C]0.077052[/C][/ROW]
[ROW][C]21[/C][C]0.015256[/C][C]0.1182[/C][C]0.453162[/C][/ROW]
[ROW][C]22[/C][C]-0.142095[/C][C]-1.1007[/C][C]0.13772[/C][/ROW]
[ROW][C]23[/C][C]-0.07273[/C][C]-0.5634[/C][C]0.287643[/C][/ROW]
[ROW][C]24[/C][C]-0.094026[/C][C]-0.7283[/C][C]0.234626[/C][/ROW]
[ROW][C]25[/C][C]-0.059688[/C][C]-0.4623[/C][C]0.322755[/C][/ROW]
[ROW][C]26[/C][C]-0.020765[/C][C]-0.1608[/C][C]0.436378[/C][/ROW]
[ROW][C]27[/C][C]0.005516[/C][C]0.0427[/C][C]0.483031[/C][/ROW]
[ROW][C]28[/C][C]0.029529[/C][C]0.2287[/C][C]0.409927[/C][/ROW]
[ROW][C]29[/C][C]-0.022961[/C][C]-0.1779[/C][C]0.429717[/C][/ROW]
[ROW][C]30[/C][C]0.118677[/C][C]0.9193[/C][C]0.180818[/C][/ROW]
[ROW][C]31[/C][C]-0.08249[/C][C]-0.639[/C][C]0.262639[/C][/ROW]
[ROW][C]32[/C][C]-0.017513[/C][C]-0.1357[/C][C]0.446273[/C][/ROW]
[ROW][C]33[/C][C]-0.025479[/C][C]-0.1974[/C][C]0.422107[/C][/ROW]
[ROW][C]34[/C][C]0.022538[/C][C]0.1746[/C][C]0.430999[/C][/ROW]
[ROW][C]35[/C][C]-0.100132[/C][C]-0.7756[/C][C]0.22051[/C][/ROW]
[ROW][C]36[/C][C]0.025999[/C][C]0.2014[/C][C]0.420538[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=61858&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61858&T=2

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.46822-3.62680.000297
2-0.515836-3.99578.9e-05
3-0.197824-1.53230.065348
4-0.052715-0.40830.342244
50.0543070.42070.337753
6-0.026723-0.2070.418357
7-0.03643-0.28220.389385
8-0.118231-0.91580.181716
9-0.02475-0.19170.424307
100.1682041.30290.098793
11-0.151148-1.17080.123156
120.1031860.79930.213642
13-0.162362-1.25770.106695
14-0.052807-0.4090.341983
15-0.030539-0.23660.406904
16-0.000494-0.00380.498478
17-0.079454-0.61550.270292
18-0.027648-0.21420.415574
190.0324330.25120.401248
20-0.186344-1.44340.077052
210.0152560.11820.453162
22-0.142095-1.10070.13772
23-0.07273-0.56340.287643
24-0.094026-0.72830.234626
25-0.059688-0.46230.322755
26-0.020765-0.16080.436378
270.0055160.04270.483031
280.0295290.22870.409927
29-0.022961-0.17790.429717
300.1186770.91930.180818
31-0.08249-0.6390.262639
32-0.017513-0.13570.446273
33-0.025479-0.19740.422107
340.0225380.17460.430999
35-0.100132-0.77560.22051
360.0259990.20140.420538


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 36 ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;
Parameters (R input):
par1 = 36 ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;
R code (references can be found in the software module):
if (par1 == 'Default') {
par1 = 10*log10(length(x))
} else {
par1 <- as.numeric(par1)
}
par2 <- as.numeric(par2)
par3 <- as.numeric(par3)
par4 <- as.numeric(par4)
par5 <- as.numeric(par5)
if (par6 == 'White Noise') par6 <- 'white' else par6 <- 'ma'
par7 <- as.numeric(par7)
if (par2 == 0) {
x <- log(x)
} else {
x <- (x ^ par2 - 1) / par2
}
if (par3 > 0) x <- diff(x,lag=1,difference=par3)
if (par4 > 0) x <- diff(x,lag=par5,difference=par4)
bitmap(file='pic1.png')
racf <- acf(x, par1, main='Autocorrelation', xlab='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep=''))
dev.off()
bitmap(file='pic2.png')
rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF')
dev.off()
(myacf <- c(racf$acf))
(mypacf <- c(rpacf$acf))
lengthx <- length(x)
sqrtn <- sqrt(lengthx)
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Autocorrelation Function',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Time lag k',header=TRUE)
a<-table.element(a,hyperlink('basics.htm','ACF(k)','click here for more information about the Autocorrelation Function'),header=TRUE)
a<-table.element(a,'T-STAT',header=TRUE)
a<-table.element(a,'P-value',header=TRUE)
a<-table.row.end(a)
for (i in 2:(par1+1)) {
a<-table.row.start(a)
a<-table.element(a,i-1,header=TRUE)
a<-table.element(a,round(myacf[i],6))
mytstat <- myacf[i]*sqrtn
a<-table.element(a,round(mytstat,4))
a<-table.element(a,round(1-pt(abs(mytstat),lengthx),6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Partial Autocorrelation Function',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Time lag k',header=TRUE)
a<-table.element(a,hyperlink('basics.htm','PACF(k)','click here for more information about the Partial Autocorrelation Function'),header=TRUE)
a<-table.element(a,'T-STAT',header=TRUE)
a<-table.element(a,'P-value',header=TRUE)
a<-table.row.end(a)
for (i in 1:par1) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
a<-table.element(a,round(mypacf[i],6))
mytstat <- mypacf[i]*sqrtn
a<-table.element(a,round(mytstat,4))
a<-table.element(a,round(1-pt(abs(mytstat),lengthx),6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable1.tab')